Abstract Traditional epidemiology cohorts have contributed greatly to our understanding of CVD and its risk factors, but concerns have been raised about their resource intensive nature, as well as their failure to integrate data from outside the research center. Digital and mobile health (mHealth) technologies provide data on individuals? behaviors, risk factors, and CVD events. The growing ubiquity of mHealth solutions provides an unprecedented opportunity to add novel ?real world? cardiovascular phenotypes to cohort studies. MHealth may facilitate more frequent, convenient, and meaningful interactions with cohort participants. Despite the availability of myriad devices, few systems have been designed to facilitate long-term cardiovascular phenotyping and CVD surveillance. We propose to enhance the FHS-NExT (Framingham Heart Study-Novel Examination using Technology) system, which includes a custom smartphone application (app) and data from a smartwatch (heart rate/steps) and digital blood pressure (BP) cuff, for use by FHS Generation 3 (Gen3) and multi-ethnic Omni 2 participants. We will identify factors associated with long-term adherence, and relations between mHealth and digital phenotypes with validated measures of fitness and arterial stiffness. Specific aims: Aim 1. Enhance the FHS-NExT smartphone app to promote adherence and compare the new FHS-NExT app CVD risk factor surveys against conventional measures in the FHS Research Center. We will enhance the FHS-NExT app, add new messaging and interactive capabilities to facilitate long-term use of the FHS-NExT app (n=2250), smartwatch (n=1500), and BP device (n=1500) and correlate FHS CVD risk score as assessed using the app to the FHS CVD risk score from the research center exam. Aim 2. Identify factors associated with successful long-term use of the FHS-NExT system, including the app, smartwatch, and digital BP device. System adherence will be defined based on: 1) app completion of lifestyle and CVD risk factor surveys every 3 months (n=2250); 2) donning the smartwatch and recording ?1000 steps daily (n=1500); and 3) taking BP measures ?once weekly (n=1500). We will identify participant or system-related factors, that affect adherence to the FHS-NExT system (n=1500 participants) over 12 months. Aim 3. Examine relations of novel exercise capacity measures by cardiopulmonary exercise testing (CPET) with average resting HR and daily step counts from smartwatch recordings over 30 days. Aim 4. Examine relations of arterial stiffness by tonometry with mean weekly BP and mean BP variability over 6 months. We bring together a highly productive, multi-disciplinary team with expertise in app development, mHealth and digital research methods and analysis, ?big data? integration, behavioral science, & CVD epidemiology. We propose to build new, scalable capabilities for digital and mHealth data collection, and test the relations between traditional in-clinic measures of cardiovascular fitness and arterial tonometry and novel mHealth phenotypes.